Brief article Statistical regularities reduce perceived numerosity Jiaying Zhao a,b,⇑ , Ru Qi Yu a a Department of Psychology, University of British Columbia, Canada b Institute for Resources, Environment and Sustainability, University of British Columbia, Canada article info Article history: Received 23 December 2014 Revised 6 September 2015 Accepted 21 September 2015 Keywords: Statistical learning Implicit learning Numerosity estimation Grouping Attention abstract Numerical information can be perceived at multiple levels (e.g., one bird, or a flock of birds). The level of input has typically been defined by explicit grouping cues, such as contours or connecting lines. Here we examine how regularities of object co-occurrences shape numerosity perception in the absence of explicit grouping cues. Participants estimated the number of colored circles in an array. We found that estimates were lower in arrays containing colors that consistently appeared next to each other across the experi- ment, even though participants were not explicitly aware of the color pairs (Experiments 1a and 1b). To provide support for grouping, we introduced color duplicates and found that estimates were lower in arrays with two identical colors (Experiment 2). The underestimation could not be explained by increased attention to individual objects (Experiment 3). These results suggest that statistical regularities reduce perceived numerosity consistent with a grouping mechanism. Ó 2015 Elsevier B.V. All rights reserved. 1. Introduction The visual system is efficient at perceiving numerical informa- tion in the environment. For instance, we can quickly approximate the number of items (Ansari, 2008; Dehaene, Dehaene-Lambertz, & Cohen, 1998; Feigenson, Dehaene, & Spelke, 2004). Since number is a discrete measure of unitized items, what determines the unit over which number is computed? The unit of input is flexible and can involve either a discrete item (e.g., one bird), or a set of items (e.g., one flock of birds). The latter is typically determined by explicit grouping cues, such as shared features (Halberda, Mazzocco, & Feigenson, 2008; Halberda, Sires, & Feigenson, 2006), categorical memberships (Feigenson, 2008; Halberda & Feigenson, 2008), spatial arrangement (Ginsburg, 1976, 1978), and segmentation (Franconeri, Bemis, & Alvarez, 2009; He, Zhang, Zhou, & Chen, 2009). The grouping cues not only define the level of input for enumer- ation, but highlight the relationships among objects, which can in turn shape numerosity perception. For instance, objects connected by lines are underestimated compared to disconnected objects (Franconeri et al., 2009; He et al., 2009). In addition to explicit grouping cues, objects can be associated in other ways. Indeed, relationships among objects are often not immediately available, but are extracted over repeated experiences. For instance, if an object always appears next to another object over multiple occasions, the joint probability between the two is 1. This reliable co-occurrence effectively associates the objects, without explicit grouping cues. One mechanism supporting the extraction of regularities is sta- tistical learning (Fiser & Aslin, 2001; Saffran, Aslin, & Newport, 1996; Turk-Browne, Jungé, & Scholl, 2005; Zhao, Al-Aidroos, & Turk-Browne, 2013). Statistical learning extracts probabilistic rela- tionships between objects over space and time, generates implicit knowledge about these relationships (Aslin & Newport, 2012; Perruchet & Pacton, 2006), and allows for chunking of objects (Brady, Konkle, & Alvarez, 2009; Kirkham, Slemmer, & Johnson, 2002; Saffran et al., 1996). An important distinction between sta- tistical learning and grouping is that the knowledge about object co-occurrences is implicit, since observers are not consciously aware of the underlying regularities (Turk-Browne, Scholl, Chun, & Johnson, 2009; Zhao et al., 2013). Given that regularities facilitate chunking, we hypothesize that statistical learning shapes numerosity perception via implicit grouping. Specifically, exposure to object co-occurrences may lead to the unitization of objects, thus reducing the perceived numeros- ity. In line with past research showing that ensemble representa- tion diminishes the perceived variability of heterogeneous stimuli (e.g., Burr & Ross, 2008; Dakin, Mareschal, & Bex, 2005; Sweeny, Haroz, & Whitney, 2013), the current study reveals how the visual system processes the complex environment and represents multiple stimuli at once. http://dx.doi.org/10.1016/j.cognition.2015.09.018 0010-0277/Ó 2015 Elsevier B.V. All rights reserved. ⇑ Corresponding author at: Department of Psychology, Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver, BC V6T 1Z4, Canada. E-mail address: jiayingz@psych.ubc.ca (J. Zhao). Cognition 146 (2016) 217–222 Contents lists available at ScienceDirect Cognition journal homepage: www.elsevier.com/locate/COGNIT